Scientists in Dresden are expanding their digital health expertise in multiple sclerosis (MS) therapy and research with an ambitious scientific project - creating a "digital twin“ from data.
Activity trackers are rising in popularity. Yet a new study demonstrates that many struggle to optimally use these devices. The cause? Outdated digital literacy skills.
A small, wearable heart monitor can detect atrial fibrillation in high-risk patients ten times more frequently than standard tests.
Sharing information about the expected effect of a health app before its use and providing positive feedback regarding its effectiveness after its use have the potential to strengthen the placebo effect.
Using mathematical image processing, scientists have found a way to create digital twins from human hearts.
Digital tracking of people with mental health conditions has the power to transform medical diagnostics and treatment, but its claims need careful scrutiny.
Researchers have created artificial intelligence algorithm that can automatically identify patients at high risk of intentional self-harm, based on the information in the clinical notes in the electronic health record.
In the next-generation operating room interconnected sensors will collect data, analyse it in real-time and make it available to digital assistance functions.
Researchers show chatbots could play a key role in helping people with issues around their health and wellbeing.
Researchers have developed a framework that will help data scientists and other researchers use better digital health tools for clinical purposes.
Pathologists who examined the computationally stained images could not tell them apart from traditionally stained slides.
“The digital transformation will make healthcare even more human. It will enable us to provide preventive and personalized healthcare,” says Prof. Dr. Koen Kas, Professor of Oncology at Ghent University, Belgium.
By adding infrared capability to the ubiquitous, standard optical microscope, researchers hope to bring cancer diagnosis into the digital era.
A new statistical technique from the field of machine learning is now making it possible to predict the success of smartphone-based interventions more accurately.
The smart insole can be inserted into a sneaker or dress shoe to passively monitor the foot health of a person living with diabetes.